{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f9c694d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "# 1 获取数据\n",
    "data = pd.read_csv(\"./data/titanic.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0c275f21",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\huishi\\AppData\\Local\\Temp\\ipykernel_24572\\366334431.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x[\"age\"].fillna(x[\"age\"].mean(), inplace=True)\n",
      "C:\\Users\\huishi\\AppData\\Local\\Temp\\ipykernel_24572\\366334431.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x[\"embarked\"].fillna(\"Unknown\", inplace=True)\n",
      "C:\\Users\\huishi\\AppData\\Local\\Temp\\ipykernel_24572\\366334431.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x[\"home.dest\"].fillna(\"Unknown\", inplace=True)\n",
      "C:\\Users\\huishi\\AppData\\Local\\Temp\\ipykernel_24572\\366334431.py:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x[\"room\"].fillna(\"Unknown\", inplace=True)\n",
      "C:\\Users\\huishi\\AppData\\Local\\Temp\\ipykernel_24572\\366334431.py:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x[\"boat\"].fillna(\"Unknown\", inplace=True)\n"
     ]
    }
   ],
   "source": [
    "# 2数据预处理\n",
    "# 划分特征值和目标值\n",
    "x = data[[\"pclass\", \"age\", \"embarked\", \"home.dest\", \"room\", \"boat\", \"sex\"]]\n",
    "y = data[\"survived\"]\n",
    "\n",
    "# 缺失值处理 home.dest room boat\n",
    "x[\"age\"].fillna(x[\"age\"].mean(), inplace=True)\n",
    "x[\"embarked\"].fillna(\"Unknown\", inplace=True)\n",
    "x[\"home.dest\"].fillna(\"Unknown\", inplace=True)\n",
    "x[\"room\"].fillna(\"Unknown\", inplace=True)\n",
    "x[\"boat\"].fillna(\"Unknown\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cc42dc99",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3特征工程\n",
    "# 特征抽取 转成字典\n",
    "x = x.to_dict(orient=\"records\")\n",
    "\n",
    "# 划分训练集和测试集\n",
    "from sklearn.model_selection import train_test_split\n",
    "x_train,x_test,y_train,y_test = train_test_split(x,y)\n",
    "\n",
    "# 字典数据结构特征抽取\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "transfor = DictVectorizer()\n",
    "x_train = transfor.fit_transform(x_train)\n",
    "x_test = transfor.transform(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e9d9ab70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'pclass': '1st',\n",
       "  'age': 29.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'St Louis, MO',\n",
       "  'room': 'B-5',\n",
       "  'boat': '2',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 2.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Montreal, PQ / Chesterville, ON',\n",
       "  'room': 'C26',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 30.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Montreal, PQ / Chesterville, ON',\n",
       "  'room': 'C26',\n",
       "  'boat': '(135)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 25.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Montreal, PQ / Chesterville, ON',\n",
       "  'room': 'C26',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 0.9167,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Montreal, PQ / Chesterville, ON',\n",
       "  'room': 'C22',\n",
       "  'boat': '11',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 47.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'E-12',\n",
       "  'boat': '3',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 63.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Hudson, NY',\n",
       "  'room': 'D-7',\n",
       "  'boat': '10',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 39.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Belfast, NI',\n",
       "  'room': 'A-36',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 58.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Bayside, Queens, NY',\n",
       "  'room': 'C-101',\n",
       "  'boat': '2',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 71.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Montevideo, Uruguay',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '(22)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 47.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '(124)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 19.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '4',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Paris, France',\n",
       "  'room': 'B-35',\n",
       "  'boat': '9',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Hessle, Yorks',\n",
       "  'room': 'A-23',\n",
       "  'boat': 'B',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 50.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Montreal, PQ',\n",
       "  'room': 'B-58/60',\n",
       "  'boat': '6',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 24.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Montreal, PQ',\n",
       "  'room': 'B-58/60',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 36.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Winnipeg, MN',\n",
       "  'room': 'C-6',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 37.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'D-35',\n",
       "  'boat': '5',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 47.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'D-35',\n",
       "  'boat': '5',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 26.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'C-148',\n",
       "  'boat': '5',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 25.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'San Francisco, CA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '(148)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 25.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Dowagiac, MI',\n",
       "  'room': 'B-49',\n",
       "  'boat': '7',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 19.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Dowagiac, MI',\n",
       "  'room': 'B-49',\n",
       "  'boat': '7',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 28.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Stockholm, Sweden / Washington, DC',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'D',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 45.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Trenton, NJ',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '(241)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 39.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Glen Ridge, NJ',\n",
       "  'room': 'A-31',\n",
       "  'boat': '7',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 30.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Youngstown, OH',\n",
       "  'room': 'C-7',\n",
       "  'boat': '8',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 58.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Birkdale, England Cleveland, Ohio',\n",
       "  'room': 'C-103',\n",
       "  'boat': '8',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'London / Winnipeg, MB',\n",
       "  'room': 'D-21/2',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 45.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Cooperstown, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '4',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 22.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'St Leonards-on-Sea, England Ohio',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '6',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Los Angeles, CA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '15',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 41.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Pomeroy, WA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 48.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Omaha, NE',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '(208)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Philadelphia, PA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 44.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Denver, CO',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '6',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 59.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Belmont, MA',\n",
       "  'room': 'C-101',\n",
       "  'boat': 'D',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 60.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Philadelphia, PA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '8',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 45.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Washington, DC',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '5/7',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 53.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Washington, DC',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '6',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 58.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Germantown, Philadelphia, PA',\n",
       "  'room': 'B-51/3/5',\n",
       "  'boat': '3',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 36.0,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Austria-Hungary / Germantown, Philadelphia, PA',\n",
       "  'room': 'B-51/3/5',\n",
       "  'boat': '3',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 33.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Montevideo, Uruguay',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Montevideo, Uruguay',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 36.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Bryn Mawr, PA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'C',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 36.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Bryn Mawr, PA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '4',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 14.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Bryn Mawr, PA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '4',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 11.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Bryn Mawr, PA',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '4',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 49.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Ascot, Berkshire / Rochester, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'New York, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '5',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 36.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Little Onn Hall, Staffs',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '(172)',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Little Onn Hall, Staffs',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '6',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 46.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Amenia, ND',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 47.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'Amenia, ND',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 27.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY / Ithaca, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '5',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.0,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'New York, NY / Ithaca, NY',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '5',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
       "  'home.dest': 'London, England',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '8',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Cherbourg',\n",
       "  'home.dest': 'Paris, France',\n",
       "  'room': 'Unknown',\n",
       "  'boat': '7',\n",
       "  'sex': 'male'},\n",
       " {'pclass': '1st',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Southampton',\n",
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       " {'pclass': '3rd',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Unknown',\n",
       "  'home.dest': 'Unknown',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'female'},\n",
       " {'pclass': '3rd',\n",
       "  'age': 31.19418104265403,\n",
       "  'embarked': 'Unknown',\n",
       "  'home.dest': 'Unknown',\n",
       "  'room': 'Unknown',\n",
       "  'boat': 'Unknown',\n",
       "  'sex': 'male'},\n",
       " ...]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3d559fb8",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'temp' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[5], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m temp\n",
      "\u001b[1;31mNameError\u001b[0m: name 'temp' is not defined"
     ]
    }
   ],
   "source": [
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "24e22606",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=10, estimator=RandomForestClassifier(),\n",
       "             param_grid={&#x27;max_depth&#x27;: [None, 5, 8, 15, 25, 30],\n",
       "                         &#x27;n_estimators&#x27;: [8, 10, 12, 14, 16]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(cv=10, estimator=RandomForestClassifier(),\n",
       "             param_grid={&#x27;max_depth&#x27;: [None, 5, 8, 15, 25, 30],\n",
       "                         &#x27;n_estimators&#x27;: [8, 10, 12, 14, 16]})</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=10, estimator=RandomForestClassifier(),\n",
       "             param_grid={'max_depth': [None, 5, 8, 15, 25, 30],\n",
       "                         'n_estimators': [8, 10, 12, 14, 16]})"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 4使用随机森林算法进行学习训练-模型\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "estimator = RandomForestClassifier()\n",
    "# 加入交叉验证和网格搜索\n",
    "super_param = {\"n_estimators\": [8,10,12,14,16], \"max_depth\": [None,5,8,15,25,30]}\n",
    "estimator = GridSearchCV(estimator=estimator,param_grid=super_param,cv=10)\n",
    "# 此处训练特征中含有3rd计算机不能处理理解 could not convert string to float: '3rd' 需要进行特征抽取\n",
    "estimator.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "661d0526",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型评估方法1：\n",
      " 965      True\n",
      "770      True\n",
      "688      True\n",
      "112      True\n",
      "1219    False\n",
      "        ...  \n",
      "741      True\n",
      "696      True\n",
      "158      True\n",
      "15       True\n",
      "974      True\n",
      "Name: survived, Length: 329, dtype: bool\n",
      "模型评估方法2,计算测试集准确率：\n",
      " 0.8875379939209727\n",
      "最佳参数：\n",
      " {'max_depth': None, 'n_estimators': 14}\n",
      "最佳结果：\n",
      " 0.8770871985157699\n",
      "最佳估计器:\n",
      " RandomForestClassifier(n_estimators=14)\n"
     ]
    }
   ],
   "source": [
    "# 5模型评估\n",
    "y_predict = estimator.predict(x_test)\n",
    "print(\"模型评估方法1：\\n\",y_predict == y_test)\n",
    "\n",
    "# 随机森林改进决策树： 0.8480243161094225 ->  0.8996960486322189 0.8966565349544073\n",
    "print(\"模型评估方法2,计算测试集准确率：\\n\",estimator.score(x_test,y_test))\n",
    "\n",
    "# 最佳参数：best_params_\n",
    "print(\"最佳参数：\\n\", estimator.best_params_)\n",
    "# 最佳结果：best_score_\n",
    "print(\"最佳结果：\\n\", estimator.best_score_)\n",
    "# 最佳估计器：best_estimator_\n",
    "print(\"最佳估计器:\\n\", estimator.best_estimator_)\n",
    "# 交叉验证结果：cv_results_\n",
    "# print(\"交叉验证结果:\\n\", estimator.cv_results_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d397e182",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0,\n",
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       "       0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0,\n",
       "       1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0,\n",
       "       0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0,\n",
       "       0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0,\n",
       "       1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0,\n",
       "       1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0],\n",
       "      dtype=int64)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b985cd4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "614     0\n",
       "959     0\n",
       "265     1\n",
       "850     0\n",
       "448     0\n",
       "       ..\n",
       "602     0\n",
       "729     1\n",
       "1206    0\n",
       "693     0\n",
       "110     1\n",
       "Name: survived, Length: 329, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba8f4001",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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